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Machine Learning

Machine Learning

前往频道在 Telegram

Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho

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📈 Telegram 频道 Machine Learning 的分析概览

频道 Machine Learning (@machinelearning9) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 40 149 名订阅者,在 技术与应用 类别中位列第 3 375,并在 叙利亚 地区排名第 227

📊 受众指标与增长动态

невідомо 创建以来,项目保持高速增长,吸引了 40 149 名订阅者。

根据 28 六月, 2026 的最新数据,频道保持稳定运转。过去 30 天订阅人数变化为 378,过去 24 小时变化为 7,整体触达仍然可观。

  • 认证状态: 未认证
  • 互动率 (ER): 平均受众互动率为 2.09%。内容发布后 24 小时内通常能获得 1.91% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 841 次浏览,首日通常累积 766 次浏览。
  • 互动与反馈: 受众积极参与,单帖平均反应数为 3
  • 主题关注点: 内容集中在 distance, insidead, gpu, learning, degree 等核心主题上。

📝 描述与内容策略

作者将该频道定位为表达主观观点的平台:
Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho

凭借高频更新(最新数据采集于 29 六月, 2026),频道始终保持新鲜度与高覆盖。分析显示受众积极互动,使其成为 技术与应用 类别中的关键影响点。

40 149
订阅者
+724 小时
+1147
+37830
帖子存档
📌 Scaling Law Of Language Models 🗂 Category: DEEP LEARNING 🕒 Date: 2024-07-09 | ⏱️ Read time: 8 min read How language mode
📌 Scaling Law Of Language Models 🗂 Category: DEEP LEARNING 🕒 Date: 2024-07-09 | ⏱️ Read time: 8 min read How language models scale with model size, training data, and training compute

📌 AI-Proof Your Data Science Skill Set by Embracing Four Timeless Concepts 🗂 Category: CAREER ADVICE 🕒 Date: 2024-07-09 |
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📌 Delta Lake Optimistic Concurrency Control: To Lock or Not to Lock? 🗂 Category: DATA ENGINEERING 🕒 Date: 2024-07-10 | ⏱️
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📌 Language Models and Spatial Reasoning: What’s Good, What Is Still Terrible, and What Is Improving 🗂 Category: PSYCHOLOGY
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📌 Heat Diffusion in a Thin Metal Rod 🗂 Category: PHYSICS 🕒 Date: 2024-07-10 | ⏱️ Read time: 7 min read What would happen i
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📌 How to Test Machine Learning Systems 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-10 | ⏱️ Read time: 18 min read From Concep
📌 How to Test Machine Learning Systems 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-10 | ⏱️ Read time: 18 min read From Concepts to Practical Code Snippets for Effective Testing

📌 Exploring Medusa and Multi-Token Prediction 🗂 Category: 🕒 Date: 2024-07-10 | ⏱️ Read time: 12 min read This blog post wi
📌 Exploring Medusa and Multi-Token Prediction 🗂 Category: 🕒 Date: 2024-07-10 | ⏱️ Read time: 12 min read This blog post will go into detail on the “MEDUSA: Simple LLM Inference Acceleration Framework…

📌 Leveraging Python Pint Units Handler Package – Part 2 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-10 | ⏱️ Read time: 10 min
📌 Leveraging Python Pint Units Handler Package – Part 2 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-10 | ⏱️ Read time: 10 min read Create your customized unit registry for physical quantities in Python

📌 Python + Google Earth Engine 🗂 Category: 🕒 Date: 2024-07-10 | ⏱️ Read time: 24 min read How to clean MapBiomas LULC rast
📌 Python + Google Earth Engine 🗂 Category: 🕒 Date: 2024-07-10 | ⏱️ Read time: 24 min read How to clean MapBiomas LULC rasters for any shapefile in Brazil

📌 A Bird’s-Eye View on the Evolution of Language Models for Text Generation 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2024
📌 A Bird’s-Eye View on the Evolution of Language Models for Text Generation 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2024-07-10 | ⏱️ Read time: 8 min read In this article I would like to share my notes on how language models (LMs)…

📌 Step-by-Step Guide to Creating Simulated Data in Python 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-10 | ⏱️ Read time: 7 mi
📌 Step-by-Step Guide to Creating Simulated Data in Python 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-10 | ⏱️ Read time: 7 min read A beginner-friendly tutorial on generating your own data for analysis and testing

📌 The Ultimate Handbook for LLM Quantization 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-07-10 | ⏱️ Read time: 17 min
📌 The Ultimate Handbook for LLM Quantization 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2024-07-10 | ⏱️ Read time: 17 min read A deep dive into LLM quantization and techniques

📌 Towards Monosemanticity: A Step Towards Understanding Large Language Models 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-07
📌 Towards Monosemanticity: A Step Towards Understanding Large Language Models 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-07-11 | ⏱️ Read time: 12 min read Understanding the mechanistic interpretability research problem and reverse-engineering these large language models

📌 Prompt Engineering for Cognitive Flexibility 🗂 Category: CHATGPT 🕒 Date: 2024-07-11 | ⏱️ Read time: 10 min read Practica
📌 Prompt Engineering for Cognitive Flexibility 🗂 Category: CHATGPT 🕒 Date: 2024-07-11 | ⏱️ Read time: 10 min read Practical insights and analysis from experiments with MMLU-Pro

📌 How to Solve an Asset Storage Problem with Mathematical Programming 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-11 | ⏱️ Rea
📌 How to Solve an Asset Storage Problem with Mathematical Programming 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-11 | ⏱️ Read time: 21 min read Solving a two-dimensional assortment problem with Python and Gurobipy

📌 What’s New in Computer Vision and Object Detection? 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-11 | ⏱️ Read time: 4 min re
📌 What’s New in Computer Vision and Object Detection? 🗂 Category: DATA SCIENCE 🕒 Date: 2024-07-11 | ⏱️ Read time: 4 min read Our weekly selection of must-read Editors’ Picks and original features

📌 Make Metrics Matter 🗂 Category: BUSINESS 🕒 Date: 2024-07-11 | ⏱️ Read time: 13 min read How data professionals can incre
📌 Make Metrics Matter 🗂 Category: BUSINESS 🕒 Date: 2024-07-11 | ⏱️ Read time: 13 min read How data professionals can increase the impact of their strongest asset

🤖🧠 15+ Gemini AI Photo Editing Prompts for Boys: Create Stunning Styles & Expressions in 2025 🗓️ 11 Oct 2025 📚 AI News &
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📌 Running Local LLMs is More Useful and Easier Than You Think 🗂 Category: 🕒 Date: 2024-07-11 | ⏱️ Read time: 6 min read A
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📌 t-Test : From Application to Theory 🗂 Category: MATHEMATICS 🕒 Date: 2024-07-12 | ⏱️ Read time: 6 min read An overview of
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